Cyberguide: a mobile context-aware tour guide
Wireless Networks - Special issue: mobile computing and networking: selected papers from MobiCom '96
Learning in graphical models
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Extending Multi-agent Cooperation by Overhearing
CooplS '01 Proceedings of the 9th International Conference on Cooperative Information Systems
Probabilistic Relational Models
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Recognizing multitasked activities from video using stochastic context-free grammar
Eighteenth national conference on Artificial intelligence
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Joint deduplication of multiple record types in relational data
Proceedings of the 14th ACM international conference on Information and knowledge management
Learning the structure of Markov logic networks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning first-order probabilistic models with combining rules
ICML '05 Proceedings of the 22nd international conference on Machine learning
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies)
Logical and Relational Learning: From ILP to MRDM (Cognitive Technologies)
Learning and inferring transportation routines
Artificial Intelligence
Statistical predicate invention
Proceedings of the 24th international conference on Machine learning
Bottom-up learning of Markov logic network structure
Proceedings of the 24th international conference on Machine learning
Modeling relationships at multiple scales to improve accuracy of large recommender systems
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Discriminative structure and parameter learning for Markov logic networks
Proceedings of the 25th international conference on Machine learning
Real world activity recognition with multiple goals
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Discriminative Structure Learning of Markov Logic Networks
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Logical Hierarchical Hidden Markov Models for Modeling User Activities
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Honest Signals: How They Shape Our World
Honest Signals: How They Shape Our World
Conditional random fields for activity recognition
Conditional random fields for activity recognition
Event Modeling and Recognition Using Markov Logic Networks
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
ACM Computing Surveys (CSUR)
Deep transfer via second-order Markov logic
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Learning Markov logic network structure via hypergraph lifting
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Modeling and Inference with Relational Dynamic Bayesian Networks
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
Learning and inferring transportation routines
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Sound and efficient inference with probabilistic and deterministic dependencies
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Joint unsupervised coreference resolution with Markov logic
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Discriminative training of Markov logic networks
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Joint inference in information extraction
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Feature selection for activity recognition in multi-robot domains
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Journal of Artificial Intelligence Research
Monitoring teams by overhearing: a multi-agent plan-recognition approach
Journal of Artificial Intelligence Research
Goal recognition through goal graph analysis
Journal of Artificial Intelligence Research
Parameter learning of logic programs for symbolic-statistical modeling
Journal of Artificial Intelligence Research
A general model for online probabilistic plan recognition
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Location-based activity recognition using relational Markov networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Collaboration and shared plans in the open world: studies of ridesharing
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Jointly identifying temporal relations with Markov Logic
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Is it really about me?: message content in social awareness streams
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Learning structure and parameters of stochastic logic programs
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Recognizing activities with multiple cues
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Probabilistic inductive logic programming
Probabilistic inductive logic programming
Probabilistic inductive logic programming
New advances in logic-based probabilistic modeling by PRISM
Probabilistic inductive logic programming
Activity recognition in desktop environments
Activity recognition in desktop environments
Bayesian role discovery for multi-agent reinforcement learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Proceedings of the 12th ACM international conference on Ubiquitous computing
Constraint propagation for efficient inference in Markov logic
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
TildeCRF: conditional random fields for logical sequences
ECML'06 Proceedings of the 17th European conference on Machine Learning
Finding your friends and following them to where you are
Proceedings of the fifth ACM international conference on Web search and data mining
A probabilistic interpretation of precision, recall and F-score, with implication for evaluation
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Event processing under uncertainty
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Complex event processing over distributed probabilistic event streams
Computers & Mathematics with Applications
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Recent research has shown that surprisingly rich models of human activity can be learned from GPS (positional) data. However, most effort to date has concentrated on modeling single individuals or statistical properties of groups of people. Moreover, prior work focused solely on modeling actual successful executions (and not failed or attempted executions) of the activities of interest. We, in contrast, take on the task of understanding human interactions, attempted interactions, and intentions from noisy sensor data in a fully relational multi-agent setting. We use a real-world game of capture the flag to illustrate our approach in a well-defined domain that involves many distinct cooperative and competitive joint activities. We model the domain using Markov logic, a statistical-relational language, and learn a theory that jointly denoises the data and infers occurrences of high-level activities, such as a player capturing an enemy. Our unified model combines constraints imposed by the geometry of the game area, the motion model of the players, and by the rules and dynamics of the game in a probabilistically and logically sound fashion. We show that while it may be impossible to directly detect a multi-agent activity due to sensor noise or malfunction, the occurrence of the activity can still be inferred by considering both its impact on the future behaviors of the people involved as well as the events that could have preceded it. Further, we show that given a model of successfully performed multi-agent activities, along with a set of examples of failed attempts at the same activities, our system automatically learns an augmented model that is capable of recognizing success and failure, as well as goals of people's actions with high accuracy. We compare our approach with other alternatives and show that our unified model, which takes into account not only relationships among individual players, but also relationships among activities over the entire length of a game, although more computationally costly, is significantly more accurate. Finally, we demonstrate that explicitly modeling unsuccessful attempts boosts performance on other important recognition tasks.